At-Home ear-EEG for early detection of AD (AHEAD)

  • Research type

    Research Study

  • Full title

    At-Home ear-EEG for early detection of Alzheimer’s Disease (AHEAD)

  • IRAS ID

    334377

  • Contact name

    Dennis Chan

  • Contact email

    dennis.chan@ucl.ac.uk

  • Sponsor organisation

    University College London

  • Clinicaltrials.gov Identifier

    Z6364106/2023/12/02, Data protection registration number

  • Duration of Study in the UK

    4 years, 0 months, 0 days

  • Research summary

    Electroencephalography (EEG) measures brain rhythms and oscillations, representing electrical manifestations of brain activity in wakefulness and sleep. In Alzheimer's disease (AD), such rhythms are affected early on and the ability to detect such changes may improve diagnosis of AD in its initial stages. Until recently, EEG usage has been restricted to hospital- and laboratory-based testing due to the bulk and complexity of the EEG kits, but major advances in engineering and technology have resulted in the development of mobile ear-EEG devices that now permit remote measurement of sleep and awake EEG with low user burden.

    The primary aim of this study is to determine whether ear-EEG can be deployed in home settings to identify early AD. Furthermore, the project has two additional aims; first, to establish the usability of in-ear devices in terms of patient acceptability, and second, to determine whether it is possible to extract from the ear-EEG data information about the nonlinear dynamics of brain states, such as oscillations and attractor properties, in order to establish whether analyses of brain states as complex systems may yield additional information on how AD may alter brain function. Finally, in a separate optional substudy, we will compare the sleep data acquired via ear-EEG in a subset of participants with the data simultaneously obtained via in a sleep lab using polysomnography to provide ground truth comparison.

    If successful, this work will have a major impact for AD research and clinical practice. The ability to collect sleep and awake EEG data at home using small mobile devices would complement current scanning and cognitive assessments and improve early diagnosis of AD in a way that is scalable for widespread clinical use. Alongside this, the ability to understand disease effect on the complex dynamics of brain states will provide unique insights into how AD affects brain activity, aiding not only early diagnosis but also providing a platform for evaluating the effectiveness of interventions aimed at preserving brain function and reducing risk of future dementia.

  • REC name

    East of Scotland Research Ethics Service REC 2

  • REC reference

    24/ES/0035

  • Date of REC Opinion

    6 Jun 2024

  • REC opinion

    Further Information Favourable Opinion